Geomorphological origin of recession curves

Abstract

[1] We identify a previously undetected link between the river network morphology and key recession curves properties through a conceptual-physical model of the drainage process of the riparian unconfined aquifer. We show that the power-law exponent, a, of −dQ/dt vs. Q curves is related to the power-law exponent of N(l) vs. G(l) curves (which we show to be connected to Hack's law), where l is the downstream distance from the channel heads, N(l) is the number of channel reaches exactly located at a distance l from their channel head, and G(l) is the total length of the network located at a distance greater or equal to l from channel heads. Using Digital Terrain Models and daily discharge observations from 67 US basins we find that geomorphologic a estimates match well the values obtained from recession curves analyses. Finally, we argue that the link between recession flows and network morphology points to an important role of low-flow discharges in shaping the channel network.

Are streamflow recession characteristics really characteristic?

“…Other studies have found comparable ranges of slope b for different purposes, e.g. between 1 and 1.6 (Palmroth et al, 2010), approximately 2 (Biswal and Marani, 2010;Shaw and Riha, 2012) or even higher than 2 (Szilagyi et al, 2007). In fact individual recession events often have larger slopes b, but those are concealed in recession plots which contain all recession events Biswal and Marani, 2010;Shaw and Riha, 2012).…”

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

“…The lateral inflow of water q is assumed to be spatially constant (e.g. Biswal and Marani, 2010;Mutzner et al, 2013).…”

On the effectiveness of recession analysis methods for capturing the characteristic storage-discharge relation: An intercomparison study

“…Storage-discharge (S-Q) relations are used to understand and predict hydrologic responses [Bart and Hope, 2014;Biswal and Marani, 2010;Ceola et al, 2010;Harman and Sivapalan, 2009;Kirchner, 2009;Palmroth et al, 2010;Rupp and Selker, 2006b;Teuling et al, 2010;Wang, 2011] and to characterize watershed properties such as drainable porosity, soil conductivity and aquifer thickness [Brutsaert and Nieber, 1977;Brutsaert and Lopez, 1998;Stoelzle et al, 2013;Szilagyi, 5 2003;Szilagyi et al, 2007]. These relations are often derived by identifying a relation between stream discharge, Q, and its time derivative, −dQ/dt, during recession periods of the hydrograph when evapotranspiration and rapid flow contributions (e.g., surface and subsurface flows) to the discharge are negligible, and streamflow is primarily determined by the catchment storage [Brutsaert and Nieber, 1977].…”

“…These relations are often derived by identifying a relation between stream discharge, Q, and its time derivative, −dQ/dt, during recession periods of the hydrograph when evapotranspiration and rapid flow contributions (e.g., surface and subsurface flows) to the discharge are negligible, and streamflow is primarily determined by the catchment storage [Brutsaert and Nieber, 1977]. The relation between −dQ/dt and Q has been derived using a multitude of recession analysis methods [Basso et al, 2015;Biswal and Marani, 2010;Brutsaert and Nieber, 1977;Kirchner, 2009;Shaw and 10 Riha, 2012;Stoelzle et al, 2013;Szilagyi et al, 2007;Teuling et al, 2010;Vogel and Kroll, 1992], which primarily differ in the procedures used to:…”

“…In contrast, Vogel and Kroll [1992], Kirchner [2009], Ceola et al [2010], Teuling et al [2010], Ajami et al [2011], Staudinger et al [2011], and Stoelzle et al [2013] fitted a regression line through 25 all the scatter points. Biswal and Marani [2010], Shaw and Riha [2012], Mutzner et al, [2013], Shaw et al [2013], Bart and Hope [2014], Biswal and Marani [2014], Biswal and Kumar [2014], and Basso et al [2015] on the other hand derived a separate regression line for each recession event using only the points from that event.…”